Reporte Data Churn

Dataset statistics

Number of variables	21
Number of observations	67190
Missing cells	333415
Missing cells (%)	23.6%
Duplicate rows	433
Duplicate rows (%)	0.6%
Total size in memory	10.3 MiB
Average record size in memory	161.0 B

Variable types

Numeric	10
Categorical	10
Boolean	1

Alerts

`MarcaVehiculo__c` has constant value "97.0"	Constant
`MdeloVehiculo__c` has constant value "999.0"	Constant
`vigencia_dias` has constant value "365"	Constant
`end_vig` has constant value "365.0"	Constant
Dataset has 433 (0.6%) duplicate rows	Duplicates
`CodigoTipoAsegurado__c` is highly correlated with `n_prod_prev`	High correlation
`PuntoVenta__c` is highly correlated with `NumeroPoliza__c` and 3 other fields	High correlation
`Producto__c` is highly correlated with `ClaseVehiculo__c` and 3 other fields	High correlation
`ClaseVehiculo__c` is highly correlated with `Producto__c` and 3 other fields	High correlation
`TipoVehiculo__c` is highly correlated with `Producto__c` and 4 other fields	High correlation
`NumeroPoliza__c` is highly correlated with `PuntoVenta__c` and 3 other fields	High correlation
`RamoTecnico__c` is highly correlated with `n_prod_prev`	High correlation
`Tipo_poliza_c` is highly correlated with `TipoVehiculo__c`	High correlation
`n_prod_prev` is highly correlated with `CodigoTipoAsegurado__c` and 6 other fields	High correlation
`total_siniestros` is highly correlated with `PuntoVenta__c` and 3 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `PuntoVenta__c` and 3 other fields	High correlation
`anios_ultimo_siniestro` is highly correlated with `PuntoVenta__c` and 2 other fields	High correlation
`PuntoVenta__c` is highly correlated with `NumeroPoliza__c` and 1 other fields	High correlation
`Producto__c` is highly correlated with `ClaseVehiculo__c` and 5 other fields	High correlation
`ClaseVehiculo__c` is highly correlated with `Producto__c` and 3 other fields	High correlation
`TipoVehiculo__c` is highly correlated with `Producto__c` and 3 other fields	High correlation
`NumeroPoliza__c` is highly correlated with `PuntoVenta__c` and 4 other fields	High correlation
`Tipo_poliza_c` is highly correlated with `NumeroPoliza__c`	High correlation
`n_prod_prev` is highly correlated with `Producto__c` and 2 other fields	High correlation
`total_siniestros` is highly correlated with `PuntoVenta__c` and 2 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `Producto__c` and 1 other fields	High correlation
`CodigoTipoAsegurado__c` is highly correlated with `n_prod_prev`	High correlation
`Producto__c` is highly correlated with `ClaseVehiculo__c` and 2 other fields	High correlation
`ClaseVehiculo__c` is highly correlated with `Producto__c` and 3 other fields	High correlation
`TipoVehiculo__c` is highly correlated with `Producto__c` and 4 other fields	High correlation
`NumeroPoliza__c` is highly correlated with `ClaseVehiculo__c` and 1 other fields	High correlation
`RamoTecnico__c` is highly correlated with `n_prod_prev`	High correlation
`Tipo_poliza_c` is highly correlated with `TipoVehiculo__c`	High correlation
`n_prod_prev` is highly correlated with `CodigoTipoAsegurado__c` and 4 other fields	High correlation
`total_siniestros` is highly correlated with `total_pagado_smmlv` and 1 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `total_siniestros` and 1 other fields	High correlation
`anios_ultimo_siniestro` is highly correlated with `total_siniestros` and 1 other fields	High correlation
`n_prod_prev` is highly correlated with `TipoVehiculo__c` and 5 other fields	High correlation
`CodigoTipoAsegurado__c` is highly correlated with `MarcaVehiculo__c` and 3 other fields	High correlation
`TipoVehiculo__c` is highly correlated with `n_prod_prev` and 5 other fields	High correlation
`tipo_poliza_name` is highly correlated with `TipoVehiculo__c` and 5 other fields	High correlation
`MarcaVehiculo__c` is highly correlated with `n_prod_prev` and 9 other fields	High correlation
`tipo_prod_desc` is highly correlated with `tipo_poliza_name` and 4 other fields	High correlation
`end_vig` is highly correlated with `n_prod_prev` and 9 other fields	High correlation
`vigencia_dias` is highly correlated with `n_prod_prev` and 9 other fields	High correlation
`FechaInicioVigencia__ctrim` is highly correlated with `MarcaVehiculo__c` and 3 other fields	High correlation
`churn` is highly correlated with `n_prod_prev` and 4 other fields	High correlation
`MdeloVehiculo__c` is highly correlated with `n_prod_prev` and 9 other fields	High correlation
`Asegurado__c` is highly correlated with `n_prod_prev` and 1 other fields	High correlation
`CodigoTipoAsegurado__c` is highly correlated with `n_prod_prev` and 1 other fields	High correlation
`PuntoVenta__c` is highly correlated with `ClaseVehiculo__c` and 1 other fields	High correlation
`Producto__c` is highly correlated with `tipo_poliza_name` and 5 other fields	High correlation
`tipo_poliza_name` is highly correlated with `Producto__c` and 11 other fields	High correlation
`tipo_prod_desc` is highly correlated with `tipo_poliza_name` and 1 other fields	High correlation
`ClaseVehiculo__c` is highly correlated with `PuntoVenta__c` and 9 other fields	High correlation
`TipoVehiculo__c` is highly correlated with `PuntoVenta__c` and 9 other fields	High correlation
`NumeroPoliza__c` is highly correlated with `Producto__c` and 7 other fields	High correlation
`FechaInicioVigencia__ctrim` is highly correlated with `tipo_poliza_name` and 3 other fields	High correlation
`RamoTecnico__c` is highly correlated with `tipo_poliza_name` and 2 other fields	High correlation
`Tipo_poliza_c` is highly correlated with `tipo_poliza_name` and 3 other fields	High correlation
`churn` is highly correlated with `tipo_poliza_name` and 4 other fields	High correlation
`n_prod_prev` is highly correlated with `Asegurado__c` and 9 other fields	High correlation
`total_siniestros` is highly correlated with `Asegurado__c` and 3 other fields	High correlation
`total_pagado_smmlv` is highly correlated with `CodigoTipoAsegurado__c` and 9 other fields	High correlation
`MarcaVehiculo__c` has 14948 (22.2%) missing values	Missing
`MdeloVehiculo__c` has 14948 (22.2%) missing values	Missing
`end_vig` has 54727 (81.5%) missing values	Missing
`n_prod_prev` has 63521 (94.5%) missing values	Missing
`total_siniestros` has 61757 (91.9%) missing values	Missing
`total_pagado_smmlv` has 61757 (91.9%) missing values	Missing
`anios_ultimo_siniestro` has 61757 (91.9%) missing values	Missing
`total_pagado_smmlv` has 736 (1.1%) zeros	Zeros

Reproduction

Analysis started	2022-05-07 15:28:17.459297
Analysis finished	2022-05-07 15:28:37.195610
Duration	19.74 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

Asegurado__c
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	54851
Distinct (%)	81.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14985354.31

Minimum	137
Maximum	22020206
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	137
5-th percentile	583868
Q1	3091077.25
median	21371430.5
Q3	21745721.75
95-th percentile	21759782.55
Maximum	22020206
Range	22020069
Interquartile range (IQR)	18654644.5

Descriptive statistics

Standard deviation	9205262.486
Coefficient of variation (CV)	0.6142839397
Kurtosis	-1.453692779
Mean	14985354.31
Median Absolute Deviation (MAD)	387952.5
Skewness	-0.717032356
Sum	1.006865956 × 10¹²
Variance	8.473685743 × 10¹³
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
583868	974	1.4%
3556455	947	1.4%
2839735	527	0.8%
3750507	436	0.6%
4022	156	0.2%
20816593	126	0.2%
20080990	106	0.2%
20107138	90	0.1%
2656485	72	0.1%
851515	62	0.1%
Other values (54841)	63694	94.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
137	1	< 0.1%
290	1	< 0.1%
411	5	< 0.1%
808	1	< 0.1%
888	9	< 0.1%
912	7	< 0.1%
963	10	< 0.1%
991	4	< 0.1%
1078	1	< 0.1%
1098	1	< 0.1%

Value	Count	Frequency (%)
22020206	1	< 0.1%
21819169	1	< 0.1%
21806303	1	< 0.1%
21805190	5	< 0.1%
21799227	1	< 0.1%
21791049	1	< 0.1%
21784011	1	< 0.1%
21778087	5	< 0.1%
21777670	5	< 0.1%
21777633	6	< 0.1%

CodigoTipoAsegurado__c
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	525.0 KiB

1	63481
4	1552
2	1352
3	805

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	67190
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	63481	94.5%
4	1552	2.3%
2	1352	2.0%
3	805	1.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	63481	94.5%
4	1552	2.3%
2	1352	2.0%
3	805	1.2%

Most occurring characters

Value	Count	Frequency (%)
1	63481	94.5%
4	1552	2.3%
2	1352	2.0%
3	805	1.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	67190	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	63481	94.5%
4	1552	2.3%
2	1352	2.0%
3	805	1.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	67190	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	63481	94.5%
4	1552	2.3%
2	1352	2.0%
3	805	1.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	67190	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	63481	94.5%
4	1552	2.3%
2	1352	2.0%
3	805	1.2%

PuntoVenta__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1394
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7373.509689

Minimum	1
Maximum	99999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	1
5-th percentile	237
Q1	1689
median	9591
Q3	12254
95-th percentile	12836.65
Maximum	99999
Range	99998
Interquartile range (IQR)	10565

Descriptive statistics

Standard deviation	5006.555375
Coefficient of variation (CV)	0.6789921742
Kurtosis	0.05391588932
Mean	7373.509689
Median Absolute Deviation (MAD)	3047
Skewness	-0.1714970568
Sum	495426116
Variance	25065596.73
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3301	2216	3.3%
7002	1883	2.8%
12190	1649	2.5%
1149	1065	1.6%
19	1000	1.5%
9721	977	1.5%
103	972	1.4%
610	966	1.4%
1503	843	1.3%
12254	836	1.2%
Other values (1384)	54783	81.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	< 0.1%
3	1	< 0.1%
5	224	0.3%
7	1	< 0.1%
8	16	< 0.1%
9	5	< 0.1%
11	1	< 0.1%
13	1	< 0.1%
14	40	0.1%
15	8	< 0.1%

Value	Count	Frequency (%)
99999	1	< 0.1%
20001	11	< 0.1%
13093	4	< 0.1%
13088	8	< 0.1%
13083	1	< 0.1%
13080	3	< 0.1%
13076	3	< 0.1%
13074	9	< 0.1%
13072	17	< 0.1%
13071	3	< 0.1%

Producto__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	47
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	85773.13701

Minimum	1
Maximum	99999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	1
5-th percentile	12
Q1	99999
median	99999
Q3	99999
95-th percentile	99999
Maximum	99999
Range	99998
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	34924.02539
Coefficient of variation (CV)	0.4071674023
Kurtosis	2.192955897
Mean	85773.13701
Median Absolute Deviation (MAD)	0
Skewness	-2.04765456
Sum	5763097076
Variance	1219687549
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=47)

Value	Count	Frequency (%)
99999	57628	85.8%
17	1576	2.3%
1	1357	2.0%
4	1182	1.8%
99	974	1.4%
95	963	1.4%
7	581	0.9%
21	513	0.8%
35	493	0.7%
93	359	0.5%
Other values (37)	1564	2.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1357	2.0%
3	4	< 0.1%
4	1182	1.8%
5	64	0.1%
6	43	0.1%
7	581	0.9%
8	16	< 0.1%
9	25	< 0.1%
10	29	< 0.1%
11	20	< 0.1%

Value	Count	Frequency (%)
99999	57628	85.8%
107	1	< 0.1%
106	3	< 0.1%
105	142	0.2%
99	974	1.4%
96	64	0.1%
95	963	1.4%
93	359	0.5%
89	25	< 0.1%
88	18	< 0.1%

tipo_poliza_name
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	14
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	525.0 KiB

s.o.a.t	52242
individual	5165
responsabilidad civil	2642
otras	2555
de daños tradicional	1138
Other values (9)	3448

Length

Max length	45
Median length	7
Mean length	8.498050305
Min length	5

Characters and Unicode

Total characters	570984
Distinct characters	22
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	responsabilidad civil
2nd row	responsabilidad civil
3rd row	otras
4th row	otras
5th row	responsabilidad civil

Common Values

Value	Count	Frequency (%)
s.o.a.t	52242	77.8%
individual	5165	7.7%
responsabilidad civil	2642	3.9%
otras	2555	3.8%
de daños tradicional	1138	1.7%
de daños	889	1.3%
de deudores hipotecarios	743	1.1%
flotante	469	0.7%
todo riesgo de obras civiles daños materiales	429	0.6%
global sector privado	412	0.6%
Other values (4)	506	0.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
s.o.a.t	52242	66.7%
individual	5165	6.6%
de	3291	4.2%
responsabilidad	2642	3.4%
civil	2642	3.4%
otras	2555	3.3%
daños	2456	3.1%
tradicional	1138	1.5%
deudores	743	0.9%
hipotecarios	743	0.9%
Other values (18)	4649	5.9%

Most occurring characters

Value	Count	Frequency (%)
.	156726	27.4%
a	74142	13.0%
o	67214	11.8%
s	66452	11.6%
t	59245	10.4%
i	32320	5.7%
d	24985	4.4%
l	14269	2.5%
e	11260	2.0%
	11076	1.9%
Other values (12)	53295	9.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	403182	70.6%
Other Punctuation	156726	27.4%
Space Separator	11076	1.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	74142	18.4%
o	67214	16.7%
s	66452	16.5%
t	59245	14.7%
i	32320	8.0%
d	24985	6.2%
l	14269	3.5%
e	11260	2.8%
r	10255	2.5%
n	9829	2.4%
Other values (10)	33211	8.2%

Other Punctuation

Value	Count	Frequency (%)
.	156726	100.0%

Space Separator

Value	Count	Frequency (%)
	11076	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	403182	70.6%
Common	167802	29.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	74142	18.4%
o	67214	16.7%
s	66452	16.5%
t	59245	14.7%
i	32320	8.0%
d	24985	6.2%
l	14269	3.5%
e	11260	2.8%
r	10255	2.5%
n	9829	2.4%
Other values (10)	33211	8.2%

Common

Value	Count	Frequency (%)
.	156726	93.4%
	11076	6.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	568528	99.6%
None	2456	0.4%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	156726	27.6%
a	74142	13.0%
o	67214	11.8%
s	66452	11.7%
t	59245	10.4%
i	32320	5.7%
d	24985	4.4%
l	14269	2.5%
e	11260	2.0%
	11076	1.9%
Other values (11)	50839	8.9%

None

Value	Count	Frequency (%)
ñ	2456	100.0%

tipo_prod_desc
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	525.0 KiB

otras	64591
convenios	1576
au excepciones	505
au ded unic liv	493
disp legales	25

Length

Max length	15
Median length	5
Mean length	5.237446049
Min length	5

Characters and Unicode

Total characters	351904
Distinct characters	17
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	otras
2nd row	otras
3rd row	otras
4th row	otras
5th row	otras

Common Values

Value	Count	Frequency (%)
otras	64591	96.1%
convenios	1576	2.3%
au excepciones	505	0.8%
au ded unic liv	493	0.7%
disp legales	25	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
otras	64591	93.3%
convenios	1576	2.3%
au	998	1.4%
excepciones	505	0.7%
ded	493	0.7%
unic	493	0.7%
liv	493	0.7%
disp	25	< 0.1%
legales	25	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
o	68248	19.4%
s	66722	19.0%
a	65614	18.6%
r	64591	18.4%
t	64591	18.4%
n	4150	1.2%
e	3634	1.0%
i	3092	0.9%
c	3079	0.9%
v	2069	0.6%
Other values (7)	6114	1.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	349895	99.4%
Space Separator	2009	0.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	68248	19.5%
s	66722	19.1%
a	65614	18.8%
r	64591	18.5%
t	64591	18.5%
n	4150	1.2%
e	3634	1.0%
i	3092	0.9%
c	3079	0.9%
v	2069	0.6%
Other values (6)	4105	1.2%

Space Separator

Value	Count	Frequency (%)
	2009	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	349895	99.4%
Common	2009	0.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	68248	19.5%
s	66722	19.1%
a	65614	18.8%
r	64591	18.5%
t	64591	18.5%
n	4150	1.2%
e	3634	1.0%
i	3092	0.9%
c	3079	0.9%
v	2069	0.6%
Other values (6)	4105	1.2%

Common

Value	Count	Frequency (%)
	2009	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	351904	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	68248	19.4%
s	66722	19.0%
a	65614	18.6%
r	64591	18.4%
t	64591	18.4%
n	4150	1.2%
e	3634	1.0%
i	3092	0.9%
c	3079	0.9%
v	2069	0.6%
Other values (7)	6114	1.7%

ClaseVehiculo__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	22248.17302

Minimum	1
Maximum	99999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	5
95-th percentile	99999
Maximum	99999
Range	99998
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	41590.09345
Coefficient of variation (CV)	1.86937118
Kurtosis	-0.2188813508
Mean	22248.17302
Median Absolute Deviation (MAD)	0
Skewness	1.334588012
Sum	1494854745
Variance	1729735873
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	46755	69.6%
99999	14948	22.2%
5	2934	4.4%
2	1426	2.1%
3	527	0.8%
7	214	0.3%
6	196	0.3%
4	105	0.2%
9	61	0.1%
8	24	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	46755	69.6%
2	1426	2.1%
3	527	0.8%
4	105	0.2%
5	2934	4.4%
6	196	0.3%
7	214	0.3%
8	24	< 0.1%
9	61	0.1%
99999	14948	22.2%

Value	Count	Frequency (%)
99999	14948	22.2%
9	61	0.1%
8	24	< 0.1%
7	214	0.3%
6	196	0.3%
5	2934	4.4%
4	105	0.2%
3	527	0.8%
2	1426	2.1%
1	46755	69.6%

MarcaVehiculo__c
Categorical

CONSTANT
HIGH CORRELATION
MISSING
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	14948
Missing (%)	22.2%
Memory size	525.0 KiB

97.0	52242

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	208968
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	97.0
2nd row	97.0
3rd row	97.0
4th row	97.0
5th row	97.0

Common Values

Value	Count	Frequency (%)
97.0	52242	77.8%
(Missing)	14948	22.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
97.0	52242	100.0%

Most occurring characters

Value	Count	Frequency (%)
9	52242	25.0%
7	52242	25.0%
.	52242	25.0%
0	52242	25.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	156726	75.0%
Other Punctuation	52242	25.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
9	52242	33.3%
7	52242	33.3%
0	52242	33.3%

Other Punctuation

Value	Count	Frequency (%)
.	52242	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	208968	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
9	52242	25.0%
7	52242	25.0%
.	52242	25.0%
0	52242	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	208968	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
9	52242	25.0%
7	52242	25.0%
.	52242	25.0%
0	52242	25.0%

MdeloVehiculo__c
Categorical

CONSTANT
HIGH CORRELATION
MISSING
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	14948
Missing (%)	22.2%
Memory size	525.0 KiB

999.0	52242

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	261210
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	999.0
2nd row	999.0
3rd row	999.0
4th row	999.0
5th row	999.0

Common Values

Value	Count	Frequency (%)
999.0	52242	77.8%
(Missing)	14948	22.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
999.0	52242	100.0%

Most occurring characters

Value	Count	Frequency (%)
9	156726	60.0%
.	52242	20.0%
0	52242	20.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	208968	80.0%
Other Punctuation	52242	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
9	156726	75.0%
0	52242	25.0%

Other Punctuation

Value	Count	Frequency (%)
.	52242	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	261210	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
9	156726	60.0%
.	52242	20.0%
0	52242	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	261210	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
9	156726	60.0%
.	52242	20.0%
0	52242	20.0%

TipoVehiculo__c
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	525.0 KiB

0	52242
99999	14948

Length

Max length	5
Median length	1
Mean length	1.88989433
Min length	1

Characters and Unicode

Total characters	126982
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	99999
2nd row	99999
3rd row	99999
4th row	99999
5th row	99999

Common Values

Value	Count	Frequency (%)
0	52242	77.8%
99999	14948	22.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	52242	77.8%
99999	14948	22.2%

Most occurring characters

Value	Count	Frequency (%)
9	74740	58.9%
0	52242	41.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	126982	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
9	74740	58.9%
0	52242	41.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	126982	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
9	74740	58.9%
0	52242	41.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	126982	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
9	74740	58.9%
0	52242	41.1%

NumeroPoliza__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	60441
Distinct (%)	90.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3884922.48

Minimum	1000002
Maximum	4845222
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	1000002
5-th percentile	1002701
Q1	4098084.25
median	4585393
Q3	4617661.75
95-th percentile	4631210.55
Maximum	4845222
Range	3845220
Interquartile range (IQR)	519577.5

Descriptive statistics

Standard deviation	1212762.246
Coefficient of variation (CV)	0.3121715432
Kurtosis	1.330058942
Mean	3884922.48
Median Absolute Deviation (MAD)	47225.5
Skewness	-1.696237083
Sum	2.610279414 × 10¹¹
Variance	1.470792265 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1001182	16	< 0.1%
1000489	14	< 0.1%
1001214	14	< 0.1%
1001176	14	< 0.1%
1004261	13	< 0.1%
1001179	13	< 0.1%
1001102	13	< 0.1%
1004259	13	< 0.1%
1001106	12	< 0.1%
1000286	12	< 0.1%
Other values (60431)	67056	99.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1000002	7	< 0.1%
1000004	7	< 0.1%
1000006	3	< 0.1%
1000007	1	< 0.1%
1000009	5	< 0.1%
1000010	5	< 0.1%
1000013	1	< 0.1%
1000014	4	< 0.1%
1000015	4	< 0.1%
1000016	5	< 0.1%

Value	Count	Frequency (%)
4845222	1	< 0.1%
4663419	1	< 0.1%
4661342	1	< 0.1%
4649462	1	< 0.1%
4649406	1	< 0.1%
4645719	1	< 0.1%
4645718	1	< 0.1%
4640593	1	< 0.1%
4634789	1	< 0.1%
4634788	1	< 0.1%

FechaInicioVigencia__ctrim
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	525.0 KiB

02-2021	63492
01-2021	3698

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	470330
Distinct characters	4
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	02-2021
2nd row	02-2021
3rd row	02-2021
4th row	02-2021
5th row	01-2021

Common Values

Value	Count	Frequency (%)
02-2021	63492	94.5%
01-2021	3698	5.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
02-2021	63492	94.5%
01-2021	3698	5.5%

Most occurring characters

Value	Count	Frequency (%)
2	197872	42.1%
0	134380	28.6%
1	70888	15.1%
-	67190	14.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	403140	85.7%
Dash Punctuation	67190	14.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	197872	49.1%
0	134380	33.3%
1	70888	17.6%

Dash Punctuation

Value	Count	Frequency (%)
-	67190	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	470330	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	197872	42.1%
0	134380	28.6%
1	70888	15.1%
-	67190	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	470330	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	197872	42.1%
0	134380	28.6%
1	70888	15.1%
-	67190	14.3%

vigencia_dias
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	525.0 KiB

365	67190

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	201570
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	365
2nd row	365
3rd row	365
4th row	365
5th row	365

Common Values

Value	Count	Frequency (%)
365	67190	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
365	67190	100.0%

Most occurring characters

Value	Count	Frequency (%)
3	67190	33.3%
6	67190	33.3%
5	67190	33.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	201570	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	67190	33.3%
6	67190	33.3%
5	67190	33.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	201570	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	67190	33.3%
6	67190	33.3%
5	67190	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	201570	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	67190	33.3%
6	67190	33.3%
5	67190	33.3%

RamoTecnico__c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	20
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.751212978

Minimum	1
Maximum	84
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	1
5-th percentile	6
Q1	8
median	8
Q3	8
95-th percentile	13
Maximum	84
Range	83
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	7.412045375
Coefficient of variation (CV)	0.8469734874
Kurtosis	89.09285772
Mean	8.751212978
Median Absolute Deviation (MAD)	0
Skewness	9.230088168
Sum	587994
Variance	54.93841665
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=20)

Value	Count	Frequency (%)
8	52242	77.8%
7	5323	7.9%
13	3738	5.6%
3	1602	2.4%
11	1595	2.4%
4	790	1.2%
1	728	1.1%
83	288	0.4%
81	212	0.3%
5	145	0.2%
Other values (10)	527	0.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	728	1.1%
2	93	0.1%
3	1602	2.4%
4	790	1.2%
5	145	0.2%
6	28	< 0.1%
7	5323	7.9%
8	52242	77.8%
11	1595	2.4%
13	3738	5.6%

Value	Count	Frequency (%)
84	129	0.2%
83	288	0.4%
81	212	0.3%
29	1	< 0.1%
23	3	< 0.1%
19	130	0.2%
18	16	< 0.1%
17	107	0.2%
15	18	< 0.1%
14	2	< 0.1%

Tipo_poliza_c
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.289090638

Minimum	1
Maximum	14
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	4
Maximum	14
Range	13
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.156473853
Coefficient of variation (CV)	0.89712377
Kurtosis	22.53680559
Mean	1.289090638
Median Absolute Deviation (MAD)	0
Skewness	4.615878672
Sum	86614
Variance	1.337431774
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	62245	92.6%
4	3107	4.6%
8	1287	1.9%
2	279	0.4%
3	225	0.3%
11	26	< 0.1%
5	17	< 0.1%
14	2	< 0.1%
6	1	< 0.1%
7	1	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	62245	92.6%
2	279	0.4%
3	225	0.3%
4	3107	4.6%
5	17	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1287	1.9%
11	26	< 0.1%
14	2	< 0.1%

Value	Count	Frequency (%)
14	2	< 0.1%
11	26	< 0.1%
8	1287	1.9%
7	1	< 0.1%
6	1	< 0.1%
5	17	< 0.1%
4	3107	4.6%
3	225	0.3%
2	279	0.4%
1	62245	92.6%

end_vig
Categorical

CONSTANT
HIGH CORRELATION
MISSING
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	54727
Missing (%)	81.5%
Memory size	525.0 KiB

365.0	12463

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	62315
Distinct characters	5
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	365.0
2nd row	365.0
3rd row	365.0
4th row	365.0
5th row	365.0

Common Values

Value	Count	Frequency (%)
365.0	12463	18.5%
(Missing)	54727	81.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
365.0	12463	100.0%

Most occurring characters

Value	Count	Frequency (%)
3	12463	20.0%
6	12463	20.0%
5	12463	20.0%
.	12463	20.0%
0	12463	20.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	49852	80.0%
Other Punctuation	12463	20.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	12463	25.0%
6	12463	25.0%
5	12463	25.0%
0	12463	25.0%

Other Punctuation

Value	Count	Frequency (%)
.	12463	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	62315	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	12463	20.0%
6	12463	20.0%
5	12463	20.0%
.	12463	20.0%
0	12463	20.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	62315	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	12463	20.0%
6	12463	20.0%
5	12463	20.0%
.	12463	20.0%
0	12463	20.0%

churn
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	65.7 KiB

True	54727
False	12463

Common Values
Category Frequency Plot

Value	Count	Frequency (%)
True	54727	81.5%
False	12463	18.5%

n_prod_prev
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	5
Distinct (%)	0.1%
Missing	63521
Missing (%)	94.5%
Memory size	525.0 KiB

1.0	1580
3.0	1038
8.0	947
2.0	94
4.0	10

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	11007
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	2.0
4th row	1.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
1.0	1580	2.4%
3.0	1038	1.5%
8.0	947	1.4%
2.0	94	0.1%
4.0	10	< 0.1%
(Missing)	63521	94.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1.0	1580	43.1%
3.0	1038	28.3%
8.0	947	25.8%
2.0	94	2.6%
4.0	10	0.3%

Most occurring characters

Value	Count	Frequency (%)
.	3669	33.3%
0	3669	33.3%
1	1580	14.4%
3	1038	9.4%
8	947	8.6%
2	94	0.9%
4	10	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	7338	66.7%
Other Punctuation	3669	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3669	50.0%
1	1580	21.5%
3	1038	14.1%
8	947	12.9%
2	94	1.3%
4	10	0.1%

Other Punctuation

Value	Count	Frequency (%)
.	3669	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	11007	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
.	3669	33.3%
0	3669	33.3%
1	1580	14.4%
3	1038	9.4%
8	947	8.6%
2	94	0.9%
4	10	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11007	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
.	3669	33.3%
0	3669	33.3%
1	1580	14.4%
3	1038	9.4%
8	947	8.6%
2	94	0.9%
4	10	0.1%

total_siniestros
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	32
Distinct (%)	0.6%
Missing	61757
Missing (%)	91.9%
Infinite	0
Infinite (%)	0.0%
Mean	42.02963372

Minimum	1
Maximum	940
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	3
median	19
Q3	38
95-th percentile	150
Maximum	940
Range	939
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	56.77385219
Coefficient of variation (CV)	1.350805305
Kurtosis	34.04193112
Mean	42.02963372
Median Absolute Deviation (MAD)	18
Skewness	3.281117197
Sum	228347
Variance	3223.270293
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
150	974	1.4%
38	948	1.4%
1	896	1.3%
37	569	0.8%
16	481	0.7%
2	273	0.4%
3	266	0.4%
4	225	0.3%
15	114	0.2%
19	106	0.2%
Other values (22)	581	0.9%
(Missing)	61757	91.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	896	1.3%
2	273	0.4%
3	266	0.4%
4	225	0.3%
5	98	0.1%
6	40	0.1%
7	81	0.1%
8	100	0.1%
9	33	< 0.1%
10	52	0.1%

Value	Count	Frequency (%)
940	3	< 0.1%
150	974	1.4%
90	2	< 0.1%
80	5	< 0.1%
52	9	< 0.1%
51	1	< 0.1%
45	6	< 0.1%
38	948	1.4%
37	569	0.8%
36	2	< 0.1%

total_pagado_smmlv
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct	386
Distinct (%)	7.1%
Missing	61757
Missing (%)	91.9%
Infinite	0
Infinite (%)	0.0%
Mean	2327.327717

Minimum	0
Maximum	55871.95629
Zeros	736
Zeros (%)	1.1%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	30.44892846
median	254.8747852
Q3	3065.269972
95-th percentile	8833.286309
Maximum	55871.95629
Range	55871.95629
Interquartile range (IQR)	3034.821043

Descriptive statistics

Standard deviation	3439.853407
Coefficient of variation (CV)	1.478027088
Kurtosis	21.66327377
Mean	2327.327717
Median Absolute Deviation (MAD)	254.8747852
Skewness	2.555526255
Sum	12644371.48
Variance	11832591.46
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
8833.286309	974	1.4%
3065.269972	947	1.4%
0	736	1.1%
1306.925184	527	0.8%
57.0596277	436	0.6%
38.70535986	156	0.2%
17.35001589	126	0.2%
207.8908871	106	0.2%
50.85823109	90	0.1%
370.2541766	72	0.1%
Other values (376)	1263	1.9%
(Missing)	61757	91.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	736	1.1%
0.1679049361	1	< 0.1%
0.225420076	2	< 0.1%
0.2439357817	1	< 0.1%
0.2557769398	1	< 0.1%
0.2844277434	1	< 0.1%
0.2931979932	1	< 0.1%
0.3073748027	1	< 0.1%
0.3077402298	1	< 0.1%
0.333331132	1	< 0.1%

Value	Count	Frequency (%)
55871.95629	2	< 0.1%
22272.9517	3	< 0.1%
8833.286309	974	1.4%
4385.698773	2	< 0.1%
3065.269972	947	1.4%
2345.751903	5	< 0.1%
2265.861102	1	< 0.1%
1556.751448	1	< 0.1%
1446.628935	1	< 0.1%
1306.925184	527	0.8%

anios_ultimo_siniestro
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	221
Distinct (%)	4.1%
Missing	61757
Missing (%)	91.9%
Infinite	0
Infinite (%)	0.0%
Mean	0.2478662864

Minimum	0.002739726027
Maximum	9.465753425
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	525.0 KiB

Quantile statistics

Minimum	0.002739726027
5-th percentile	0.002739726027
Q1	0.005479452055
median	0.008219178082
Q3	0.07671232877
95-th percentile	1.452054795
Maximum	9.465753425
Range	9.463013699
Interquartile range (IQR)	0.07123287671

Descriptive statistics

Standard deviation	0.9094300083
Coefficient of variation (CV)	3.66903471
Kurtosis	38.02820082
Mean	0.2478662864
Median Absolute Deviation (MAD)	0.005479452055
Skewness	5.773418116
Sum	1346.657534
Variance	0.82706294
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.008219178082	1094	1.6%
0.002739726027	991	1.5%
0.005479452055	742	1.1%
0.01095890411	563	0.8%
0.1095890411	182	0.3%
0.09315068493	138	0.2%
0.07123287671	87	0.1%
0.07671232877	68	0.1%
0.01643835616	58	0.1%
0.02465753425	56	0.1%
Other values (211)	1454	2.2%
(Missing)	61757	91.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.002739726027	991	1.5%
0.005479452055	742	1.1%
0.008219178082	1094	1.6%
0.01095890411	563	0.8%
0.01369863014	39	0.1%
0.01643835616	58	0.1%
0.02191780822	15	< 0.1%
0.02465753425	56	0.1%
0.02739726027	7	< 0.1%
0.0301369863	25	< 0.1%

Value	Count	Frequency (%)
9.465753425	1	< 0.1%
8.75890411	7	< 0.1%
8	7	< 0.1%
7.531506849	2	< 0.1%
7.178082192	6	< 0.1%
7.101369863	3	< 0.1%
7.005479452	3	< 0.1%
6.994520548	1	< 0.1%
6.235616438	12	< 0.1%
6.008219178	7	< 0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Asegurado__c	CodigoTipoAsegurado__c	PuntoVenta__c	Producto__c	tipo_poliza_name	tipo_prod_desc	ClaseVehiculo__c	MarcaVehiculo__c	MdeloVehiculo__c	TipoVehiculo__c	NumeroPoliza__c	FechaInicioVigencia__ctrim	vigencia_dias	RamoTecnico__c	Tipo_poliza_c	end_vig	churn	n_prod_prev	total_siniestros	total_pagado_smmlv	anios_ultimo_siniestro
0	715728	2	7002	4	responsabilidad civil	otras	99999	NaN	NaN	99999	1008501	02-2021	365	13	1	365.0	False	1.0	36.0	517.127899	0.005479
1	715728	2	7002	4	responsabilidad civil	otras	99999	NaN	NaN	99999	1008489	02-2021	365	13	1	365.0	False	1.0	36.0	517.127899	0.005479
2	3514	1	3202	99999	otras	otras	99999	NaN	NaN	99999	1001143	02-2021	365	15	1	NaN	True	NaN	NaN	NaN	NaN
3	249737	1	3202	99999	otras	otras	99999	NaN	NaN	99999	1001144	02-2021	365	15	1	NaN	True	NaN	NaN	NaN	NaN
4	20043213	1	3202	1	responsabilidad civil	otras	99999	NaN	NaN	99999	1060151	01-2021	365	13	1	NaN	True	2.0	1.0	254.588224	0.005479
5	20005898	1	3202	1	responsabilidad civil	otras	99999	NaN	NaN	99999	1060152	01-2021	365	13	1	NaN	True	1.0	1.0	0.000000	0.394521
6	3511668	1	3202	1	responsabilidad civil	otras	99999	NaN	NaN	99999	1060153	01-2021	365	13	1	NaN	True	2.0	1.0	0.000000	0.063014
7	20492197	1	3202	1	responsabilidad civil	otras	99999	NaN	NaN	99999	1060154	01-2021	365	13	1	NaN	True	2.0	NaN	NaN	NaN
8	2468858	1	3202	1	responsabilidad civil	otras	99999	NaN	NaN	99999	1060155	01-2021	365	13	1	NaN	True	2.0	1.0	4385.698773	1.841096
9	20492197	1	3202	31	responsabilidad civil	otras	99999	NaN	NaN	99999	1060187	01-2021	365	13	1	365.0	False	2.0	NaN	NaN	NaN

Last rows

	Asegurado__c	CodigoTipoAsegurado__c	PuntoVenta__c	Producto__c	tipo_poliza_name	tipo_prod_desc	ClaseVehiculo__c	MarcaVehiculo__c	MdeloVehiculo__c	TipoVehiculo__c	NumeroPoliza__c	FechaInicioVigencia__ctrim	vigencia_dias	RamoTecnico__c	Tipo_poliza_c	end_vig	churn	n_prod_prev	total_siniestros	total_pagado_smmlv	anios_ultimo_siniestro
67180	222512	1	3301	99999	todo riesgo de obras civiles daños materiales	otras	99999	NaN	NaN	99999	1004711	01-2021	365	3	8	365.0	False	NaN	NaN	NaN	NaN
67181	222512	1	3301	99999	otras	otras	99999	NaN	NaN	99999	1004711	01-2021	365	11	8	365.0	False	NaN	NaN	NaN	NaN
67182	222512	1	3301	1	otras	otras	99999	NaN	NaN	99999	1004711	01-2021	365	13	8	365.0	False	NaN	NaN	NaN	NaN
67183	583868	1	9721	99	individual	otras	99999	NaN	NaN	99999	3173056	02-2021	365	7	1	NaN	True	3.0	150.0	8833.286309	0.00274
67184	459479	1	3201	17	individual	convenios	99999	NaN	NaN	99999	3173059	01-2021	365	7	1	365.0	False	NaN	NaN	NaN	NaN
67185	1982298	1	19	99999	s.o.a.t	otras	2	97.0	999.0	0	4573822	01-2021	365	8	1	365.0	False	NaN	NaN	NaN	NaN
67186	1876061	1	3202	17	individual	convenios	99999	NaN	NaN	99999	3129700	01-2021	365	7	1	NaN	True	NaN	NaN	NaN	NaN
67187	20025245	1	404	13	colectiva	otras	99999	NaN	NaN	99999	3034376	01-2021	365	7	2	NaN	True	1.0	NaN	NaN	NaN
67188	1135900	1	1820	95	individual	otras	99999	NaN	NaN	99999	3075907	01-2021	365	7	1	NaN	True	NaN	NaN	NaN	NaN
67189	20713284	1	3303	99999	s.o.a.t	otras	1	97.0	999.0	0	4595162	02-2021	365	8	1	NaN	True	NaN	NaN	NaN	NaN

Most frequently occurring

	Asegurado__c	CodigoTipoAsegurado__c	PuntoVenta__c	Producto__c	tipo_poliza_name	tipo_prod_desc	ClaseVehiculo__c	MarcaVehiculo__c	MdeloVehiculo__c	NumeroPoliza__c	FechaInicioVigencia__ctrim	vigencia_dias	RamoTecnico__c	Tipo_poliza_c	end_vig	churn	n_prod_prev	total_siniestros	total_pagado_smmlv	anios_ultimo_siniestro	# duplicates
0	1923	2	7002	99999	s.o.a.t	otras	2	97.0	999.0	4099550	01-2021	365	8	1	365.0	False	1.0	7.0	28.361440	0.010959	2
1	2598	4	7002	99999	s.o.a.t	otras	3	97.0	999.0	4098576	02-2021	365	8	1	365.0	False	1.0	7.0	222.795244	0.106849	2
2	2598	4	7002	99999	s.o.a.t	otras	3	97.0	999.0	4098577	02-2021	365	8	1	365.0	False	1.0	7.0	222.795244	0.106849	2
3	4022	2	301	99999	s.o.a.t	otras	1	97.0	999.0	4150858	02-2021	365	8	1	365.0	False	1.0	4.0	38.705360	0.109589	2
4	4022	2	301	99999	s.o.a.t	otras	1	97.0	999.0	4150859	02-2021	365	8	1	365.0	False	1.0	4.0	38.705360	0.109589	2
5	4022	2	301	99999	s.o.a.t	otras	1	97.0	999.0	4150860	02-2021	365	8	1	365.0	False	1.0	4.0	38.705360	0.109589	2
6	4022	2	301	99999	s.o.a.t	otras	1	97.0	999.0	4150861	02-2021	365	8	1	365.0	False	1.0	4.0	38.705360	0.109589	2
7	4022	2	301	99999	s.o.a.t	otras	1	97.0	999.0	4150862	02-2021	365	8	1	365.0	False	1.0	4.0	38.705360	0.109589	2
8	4022	2	301	99999	s.o.a.t	otras	1	97.0	999.0	4150863	02-2021	365	8	1	365.0	False	1.0	4.0	38.705360	0.109589	2
9	4022	2	301	99999	s.o.a.t	otras	1	97.0	999.0	4150864	02-2021	365	8	1	365.0	False	1.0	4.0	38.705360	0.109589	2

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Other Punctuation

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

None

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category